Evaluation of the innovation transformation efficiency of Chinese listed SRDI enterprises based on an improved dynamic three-stage network SBM-DEA model
Specialised, refined, distinctive, and innovative (SRDI) enterprises hold profound strategic significance for advancing China’s high-quality economic development. However, SRDI enterprises face challenges in translating innovation outcomes into practical value, and their innovation transformation efficiency (ITE) has yet to be fully explored. Therefore, this study aims to identify critical weaknesses of SRDI enterprises and to formulate adaptive strategies for enhancing their ITE. A novel evaluation system is proposed, grounded in the synergy among R&D applications, R&D authorisations, and commercial transformation. This system is employed to assess the ITE by adopting an improved dynamic three-stage network slack-based measure data envelopment analysis (SBM-DEA) model. Analysis of SRDI enterprises from 2019 to 2023 reveals three main findings: (1) The overall ITE remains low, attributable to the fact that innovation R&D efficiency (IRDE) and commercial transformation efficiency (CTE) are clustered around low mean values in most provinces. (2) Over the five-year period, IRDE is observed to be stronger than CTE, with the latter demonstrating the weakest results. (3) Significant regional heterogeneity exists, with SRDI enterprises in the eastern and western regions exhibiting higher ITE than those in other regions. These findings underscore the need for tailored policy recommendations for SRDI enterprises in different regions.
Authors
- Meijuan Li (ORCID: https://orcid.org/0000-0002-1037-3615)
- Hongcheng Xu
- Ning Yuan
- Wei Yang
Institutions
- Fuzhou University (CN)
Publication Details
- Journal
- Technology Analysis and Strategic Management
- Published
- 2026-10-15
- DOI
- https://doi.org/10.1080/09537325.2026.2742996
- Primary Topic
- Efficiency Analysis Using DEA
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- National Natural Science Foundation of China
- Natural Science Foundation of Fujian Province